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What is hyper-geometic probability?
The hyper-geometric distribution is a discrete probability distribution which is similar (in some respects) to the binomial distribution. Suppose you have a population of N which contains R successes. The Binomial describes the probability of r successes in n draws out on N with replacement.However, in many situations the draw is not replaced. In this case you get the hyper-geometric distribution.The function is given by:Prob(r successes in n draws out of N) = RCr/[N-RCn-r * NCn]With the binomial distribution the probability of success remains constant (=R/N) throughout. With the hypergeometric, the numerator for success reduces by one after each successful outcome whereas the denominator reduces by one whatever the outcome.
Moment generating function of a negative binomial distribution?
[(1 - p)/(1 - pet)]r for t < -ln(p) where p = probability of success in each trial, r = number of failures before success.
What is sampling distribution of a statistic called?
The parent probability distribution from which the statistic was calculated is referred to as f(x) and cumulative distribution function as F(x). The sampling distribution and cumulative distribution of a statistic is commonly referred to as g(y) and G(y) where Y is the random variable representing the statistic. There are numerous other notations.
How can one determine the median from a graph?
The answer depends on what the graph is of: the distribution function or the cumulative distribution function.
Which distribution function has equal mean and variance?
The exponential distribution and the Poisson distribution.
